Skip to main content
SpringerLink
Log in
Book cover

Global Virology III: Virology in the 21st Century pp 41–57Cite as

Non-immune Modulators of Cellular Immune Surveillance to HIV-1 and Other Retroviruses: Future Artificial Intelligence-Driven Goals and Directions

  • Chapter
  • First Online:

  • 985 Accesses

Abstract

Immune surveillance to viruses and other foreign pathogens involves a specific process, which is well-characterized in terms of the immune and non-immune cells and factors involved, and their specific timeline. For example, first exposure to a viral antigen involves major histocompatibility complex type I molecules to present the ‘self’ and ‘nonself’ antigen to CD3 + CD8 + CD45RA+ T cells. This presentation initiates the event of T cell activation, which results in the production of T cell growth factor (interleukin 2, IL-2), interferon-gamma (IFN-g) and other immune soluble products, which together act to promote the clonal proliferative expansion of the responding cell population. Soluble immune factors produced during this initial phase of the immune response also initiate the maturation of the responding T cells into CD3 + CD8 + CD45R0+ memory cells against that specific viral antigen, and of related cell populations that act to control and dampen cellular immune reactivity. Contemporaneously, these soluble immune factors trigger non-immune cells to release of non-immune soluble factors, including pituitary and adrenocortical hormones (e.g., glucocorticoids), which finely modulate immune cell responses. Together, immune and non-immune cells and soluble factors act in concert to engender and sustain a finely tuned immune surveillance process, whose ultimate end (Y) is to regain homeostatic balance of the organism – a healthy state, that is eradication of the immune-pathological signs and symptoms that derived from the viral infection, referring here to homeostatic balance Y.

In brief, immune and non-immune cells and soluble factors are concerted predicting factors for regaining Y, to the same extent as the initial viral challenge, and other factors related to the state of heterostasis of the organism. These states, which include unhealthy eating habits, sleep deprivation, stress, and the like, act in concert to delay, hamper and counter Y.

Therefore, from a biostatistical viewpoint, the problem becomes a relatively basic multiple regression, in which the outcome Y, the homeostatic state of health regained following a viral infection, is simply the sum of positive and negative factors and/or events. Positive factors and events (Π) inherently push allostasis forward (i.e., the orderly process of immune activation and maturation), but the negative (Ν) factors and events, allostatically speaking, interfere with attaining Y. Simplistically, Y is the product of the fine, coordinated and time-regulated interaction between all the interacting Π’s and Ν’s during the immune surveillance process (Y = ΣΠ + ΣΝ).

The question then becomes, knowing what we know today about the constituents of ΣΠ and of ΣΝ, can we not design, by means of bioinformatics, artificial Π’s and Ν’s, that may push the organism’s response more securely through all the allostatic phases to Y, the homeostatic state of health regained following a viral infection? Physiology has been able to a related feat by producing bioinformatics particles, which when injected in patients help regulate cholesterol levels. Future artificial intelligence (AI) advances will produce the artificial Π’s and Ν’s, which will aid regaining Y. In the meanwhile, as science continues to complete our knowledge of all the Π’s and of all the Ν’s involved, “tweening”, the computerized process by which, knowing the end-product of a sequence, the steps in-between can be programmed, will be applied to our conceptualization of immune surveillance events.

In conclusion, the novel science of immune-tweening will helps us understand and complete a set of immune and non-immune events that lead to Y, the homeostatic state of health regained following a viral infection. AI, on the other hand, holds strong promise to help us generate and produce bioinformatics or ‘micro-adjuvants’, as it were, of immune surveillance. We envisage that these giant steps in the future of viral immunity will first be achieved in the context of infection with the human immunodeficiency virus (HIV) because it has become the model for our understanding of anti-viral immune surveillance.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Chiappelli F. Immunophysiological role and clinical implications of non-immunoglobulin soluble products of immune effector cells. Adv Neuroimmunol. 1991;1:234–40.

    Article  Google Scholar 

  2. Barkhodarian A, Thames AD, Du AM, Jan AL, Nahcivan M, Nguyen MT, Sama N, Chiappelli F. Viral immune surveillance: toward a TH17/TH9 gate to the central nervous system. Bioinformation. 2015;11:47–54.

    Article  Google Scholar 

  3. Murphy K, Weaver C. Janeway Immunobiology. 9th ed. New York, NY: Garland Science/Taylor & Francis Group; 2017.

    Google Scholar 

  4. Chiappelli F, Manfrini E, Gwirtsman H, Garcia C, Pham L, Lee P, Frost P. Steroid receptor-mediated modulation of CD4+CD62L+ cell homing. Implications for drug abusers. Ann N Y Acad Sci. 1994;746:421–5.

    Article  CAS  PubMed  Google Scholar 

  5. Chiappelli F, Kung MA. Immune surveillance of the oral cavity and lymphocyte migration: relevance for alcohol abusers. Lymphology. 1995;28(4):196–207.

    CAS  PubMed  Google Scholar 

  6. Angeli V, Randolph GJ. Inflammation, lymphatic function, and dendritic cell migration. Lymphat Res Biol. 2006;4(4):217–28.

    Article  CAS  PubMed  Google Scholar 

  7. Liao S, von der Weid PY. Lymphatic system: an active pathway for immune protection. Semin Cell Dev Biol. 2015;38:83–9.

    Article  CAS  PubMed  Google Scholar 

  8. Randolph GJ, Ivanov S, Zinselmeyer BH, Scallan JP. The lymphatic system: integral roles in immunity. Annu Rev Immunol. 2017;35:31–52.

    Article  CAS  PubMed  Google Scholar 

  9. Ryter A. Relationship between ultrastructure and specific functions of macrophages. Comp Immunol Microbiol Infect Dis. 1985;8(2):119–33.

    Article  CAS  PubMed  Google Scholar 

  10. Langermans JA, Hazenbos WL, van Furth R. Antimicrobial functions of mononuclear phagocytes. J Immunol Methods. 1994;174(1–2):185–94.

    Article  CAS  PubMed  Google Scholar 

  11. Withers DR. Innate lymphoid cell regulation of adaptive immunity. Immunology. 2016;149:123–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Burnet FM. Cellular immunology: self and notself. Cambridge: Cambridge University Press; 1969.

    Google Scholar 

  13. Bretscher P, Cohn M. A theory of self-nonself discrimination. Science. 1970;169(3950):1042–9.

    CAS  PubMed  Google Scholar 

  14. Chiappelli F, Gormley GJ, Gwirstman HE, Lowy MT, Nguyen LD, Nguyen L, Esmail I, Strober M, Weiner H. Effects of intravenous and oral dexamethasone on selected lymphocyte subpopulations in normal subjects. Psychoneuroendocrinology. 1992;17(2–3):145–52.

    Article  CAS  PubMed  Google Scholar 

  15. Chiappelli F, Kung M, Lee P, Pham L, Manfrini E, Villanueva P. Alcohol modulation of human normal T-cell activation, maturation, and migration. Alcohol Clin Exp Res. 1995;19(3):539–44.

    Article  CAS  PubMed  Google Scholar 

  16. Abbas AK, Murphy KM, Sher A. Functional diversity of helper T lymphocytes. Nature. 1996;383(6603):787–93.

    Article  CAS  PubMed  Google Scholar 

  17. Grewal IS, Flavell RA. CD40 and CD154 in cell-mediated immunity. Annu Rev Immunol. 1998;16(1):111–35.

    Article  CAS  PubMed  Google Scholar 

  18. Langman RE, Cohn M. A minimal model for the self-nonself discrimination: a return to the basics. Semin Immunol. 2000;12(3):189–95.

    Article  CAS  PubMed  Google Scholar 

  19. Guermonprez P, Valladeau J, Zitvogel L, Théry C, Amigorena S. Antigen presentation and T cell stimulation by dendritic cells. Annu Rev Immunol. 2002;20(1):621–67.

    Article  CAS  PubMed  Google Scholar 

  20. Holtmeier W, Kabelitz D. gammadelta T cells link innate and adaptive immune responses. Chem Immunol Allergy. 2005;86:151–83.

    Article  CAS  PubMed  Google Scholar 

  21. Girardi M. Immunosurveillance and immunoregulation by gammadelta T cells. J Invest Dermatol. 2006;126(1):25–31.

    Article  CAS  PubMed  Google Scholar 

  22. Andersen MH, Schrama D, Thor Straten P, Becker JC. Cytotoxic T cells. J Invest Dermatol. 2006;126(1):32–41.

    Article  CAS  PubMed  Google Scholar 

  23. Copeland KF, Heeney JL. T helper cell activation and human retroviral pathogenesis. Microbiol Rev. 1996;60(4):722–42.

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Kawai T, Akira S. Innate immune recognition of viral infection. Nat Immunol. 2006;7(2):131–7.

    Article  CAS  PubMed  Google Scholar 

  25. Restifo NP, Gattinoni L. Lineage relationship of effector and memory T cells. Curr Opin Immunol. 2013;25(5):556–63.

    Article  CAS  PubMed  Google Scholar 

  26. Sall FB, Germini D, Kovina AP, Ribrag V, Wiels J, Toure AO, Iarovaia OV, Lipinski M, Vassetzky Y. Effect of environmental factors on nuclear organization and transformation of human B lymphocytes. Biochemistry (Mosc). 2018;83(4):402–10.

    Article  CAS  Google Scholar 

  27. Kurosaki T, Kometani K, Ise W. Memory B cells. Nat Rev Immunol. 2015;15(3):149–59.

    Article  CAS  PubMed  Google Scholar 

  28. Seliger B, Ritz U, Ferrone S. Molecular mechanisms of HLA class I antigen abnormalities following viral infection and transformation. Int J Cancer. 2006;118(1):129–38.

    Article  CAS  PubMed  Google Scholar 

  29. Walker B, McMichael A. The T-cell response to HIV. Cold Spring Harb Perspect Med. 2012;2(11):a007054.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  30. Braciale TJ, Hahn YS. Immunity to viruses. Immunol Rev. 2013;255(1):10.1111–12109.

    Article  CAS  Google Scholar 

  31. Wortzman ME, Clouthier DL, McPherson AJ, Lin GH, Watts TH. The contextual role of TNFR family members in CD8(+) T-cell control of viral infections. Immunol Rev. 2013;255(1):125–48.

    Article  CAS  PubMed  Google Scholar 

  32. Harris JF, Micheva-Viteva S, Li N, Hong-Geller E. Small RNA-mediated regulation of host-pathogen interactions. Virulence. 2013;4(8):785–95.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Tacchetti C, Favre A, Moresco L, Meszaros P, Luzzi P, Truini M, Rizzo F, Grossi CE, Ciccone E. HIV is trapped and masked in the cytoplasm of lymph node follicular dendritic cells. Am J Pathol. 1997;150(2):533–42.

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Price RW, Brew B, Sidtis J, Rosenblum M, Scheck AC, Cleary P. The brain in AIDS: central nervous system HIV-1 infection and AIDS dementia complex. Science. 1988;239(4840):586–92.

    Article  CAS  PubMed  Google Scholar 

  35. Chiappelli F, Kung MA, Villanueva P. Neuropsychoimmunology of drugs of abuse and AIDS. J Neuroimmunol. 1996;69:48–9.

    Google Scholar 

  36. Minagar A, Commins D, Alexander JS, Hoque R, Chiappelli F, Singer EJ, Nikbin B, Shapshak P. NeuroAIDS: characteristics and diagnosis of the neurological complications of AIDS. Mol Diagn Ther. 2008;12(1):25–43.

    Article  CAS  PubMed  Google Scholar 

  37. Shapshak P, Chiappelli F, Commins D, Singer E, Levine AJ, Somboonwit C, Minagar A, Pellionisz AJ. Molecular epigenetics, chromatin, and NeuroAIDS/HIV: translational implications. Bioinformation. 2008;3(1):53–7.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Chiappelli F, Shapshak P, Commins D, Singer E, Minagar A, Oluwadara O, Prolo P, Pellionisz AJ. Molecular epigenetics, chromatin, and NeuroAIDS/HIV: immunopathological implications. Bioinformation. 2008;3(1):47–52.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Chiappelli F. Psychoneuroimmunology of immune reconstitution inflammatory syndrome (IRIS): the new frontier in translational biomedicine. Transl Biomed. 2015;6:11–4.

    Google Scholar 

  40. Chiappelli F, Bakhordarian A, Thames AD, Du AM, Jan AL, Nahcivan M, Nguyen MT, Sama N, Manfrini E, Piva F, Rocha RM, Maida CA. Ebola: translational science considerations. J Transl Med. 2015;13:11.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Chiappelli F, Franceschi C, Ottaviani E, Solomon GF, Taylor AN. Neuroendocrine modulation of the immune system. In: Greger R, Koepchen HP, Mommaerts W, Winhorst U, editors. Human physiology: from cellular mechanisms to integration. New York: Springer; 1996. p. 1707–29, Section L Chapter 86.

    Chapter  Google Scholar 

  42. Chiappelli F, Abanomy A, Hodgson D, Mazey KA, Messadi DV, Mito RS, Nishimura I, Spigleman I. Clinical, experimental and translational psychoneuroimmunology research models in oral biology and medicine. In: Ader R, et al., editors. Psychoneuroimmunology, vol. III: Academic Press; 2001. p. 645–70, Chapter 64.

    Google Scholar 

  43. Prolo P, Chiappelli F, Fiorucci A, Dovio A, Sartori ML, Angeli A. Psychoneuroimmunology: new avenues of research for the 21st century. Ann N Y Acad Sci. 2002;966:400–8.

    Article  CAS  PubMed  Google Scholar 

  44. Chiappelli F, Prolo P, Fiala M, Cajulis O, Iribarren J, Panerai A, Neagos N, Younai F, Bernard G. Allostasis in HIV infection and AIDS. In: Minagar PA, Shapshak P, editors. Neuro-AIDS: Nova Science Publisher, Inc.; 2006. p. 121–65, Chapter VI.

    Google Scholar 

  45. Barkhordarian A, Ajaj R, Ramchandani MH, Demerjian G, Cayabyab R, Danaie S, Ghodousi N, Iyer N, Mahanian N, Phi L, Giroux A, Manfrini E, Neagos N, Siddiqui M, Cajulis OS, Brant X, Shapshak P, Chiappelli F. Osteoimmunopathology in HIV/AIDS: a translational evidence-based perspective. Pathol Res Int. 2011, Article ID 359242 epub 21 May 2011.

    Google Scholar 

  46. Chiappelli F, Kutschman MM. Current and Future Directions in Psychobiology. In: Chiappelli F, editor. Advances in Psychobiology. Hauppauge, NY: NovaScience Publisher, Inc.; 2018, Chapter 1.

    Google Scholar 

  47. Chiappelli F, Cajulis OS. Psychobiological views on “stress-related oral ulcers”. Quintessence Int. 2004;35:223–7.

    PubMed  Google Scholar 

  48. Turner-Cobb JM. Psychological and stress hormone correlates in early life: a key to HPA-axis dysregulation and normalization. Stress. 2005;8(1):47–57.

    Article  CAS  PubMed  Google Scholar 

  49. Chiappelli F, Trignani S. Neuroendocrine-immune interactions: implications for clinical research. Adv Biosci. 1993;90:185–98.

    Google Scholar 

  50. Chiappelli F, Manfrini E, Franceschi C, Cossarizza A, Black K. Steroid regulation of cytokines: relevance for TH1→TH2 shift? Ann N Y Acad Sci. 1994;746:204–16.

    Article  CAS  PubMed  Google Scholar 

  51. Chiappelli F, Liu NQ. Non-mammalian models of neuroendocrine-immune modulation: relevance for research in oral biology and medicine. Int J Oral Biol. 1999;24:47–61.

    Google Scholar 

  52. Elenkov IJ, Wilder RL, Chrousos GP, Vizi ES. The sympathetic nerve--an integrative interface between two supersystems: the brain and the immune system. Pharmacol Rev. 2000;52(4):595–638.

    CAS  PubMed  Google Scholar 

  53. Romeo HE, Tio DL, Rahman SU, Chiappelli F, Taylor AN. The glossopharyngeal nerve as a novel pathway in immune-to-brain communication: relevance to neuroimmune surveillance of the oral cavity. J Neuroimmunol. 2001;115:91–100.

    Article  CAS  PubMed  Google Scholar 

  54. Yun AJ, Lee PY, Bazar KA. Modulation of host immunity by HIV may be partly achieved through usurping host autonomic functions. Med Hypotheses. 2004;63:362–6.

    Article  CAS  PubMed  Google Scholar 

  55. Chiappelli F, Alwan J, Prolo P, Christensen R, Fiala M, Cajulis OS, Bernard G. Neuro-immunity in stress-related oral ulcerations: a fractal analysis. Front Biosci. 2005;10:3034–41.

    Article  CAS  PubMed  Google Scholar 

  56. Angeli A, Dovio A, Sartori ML, Masera RG, Ceoloni B, Prolo P, Racca S, Chiappelli F. Interactions between glucocorticoids and cytokines in the bone microenvironment. Ann N Y Acad Sci. 2002;966:97–107.

    Article  CAS  PubMed  Google Scholar 

  57. Kenney MJ, Ganta CK. Autonomic nervous system and immune system interactions. Compr Physiol. 2014;4:1177–200.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Chiappelli F, Bakhordarian A, Bach Q, Demerjian GG. Translational psychoneuroimmunology in oral biology & medicine. For Immunopathol Dis Therap. 2016;6:119–32.

    Google Scholar 

  59. Khakshooy A, Chiappelli F. Hypothalamus-pituitary-adrenal - cell-mediated immunity regulation in the immune restoration inflammatory syndrome. Bioinformation. 2016;12:28–30.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Diazzi C, Brigante G, Ferrannini G, Ansaloni A, Zirilli L, De Santis MC, Zona S, Guaraldi G, Rochira V. Pituitary growth hormone (GH) secretion is partially rescued in HIV-infected patients with GH deficiency (GHD) compared to hypopituitary patients. Endocrine. 2017;55:885–98.

    Article  CAS  PubMed  Google Scholar 

  61. Chiappelli F. Fundamentals of evidence-based health care and translational science. Heidelberg: Springer; 2014.

    Book  Google Scholar 

  62. Khakshooy A, Chiappelli F, editors. Practical biostatistics in translational healthcare. New York, NY: Springer; 2018.

    Google Scholar 

  63. Draper NR, Smith H. Applied regression analysis. 3rd ed. Hoboken, NJ: John Wiley; 1998.

    Book  Google Scholar 

  64. Bingham NH, Fry JM. Regression: linear models in statistics. Heidelberg: Springer; 2010.

    Book  Google Scholar 

  65. Donald BR. Algorithms in structural molecular biology. Cambridge, MA: The MIT Press; 2011.

    Google Scholar 

  66. Russell SJ, Norvig P. Artificial intelligence: a modern approach. Englewood Cliffs, N.J: Prentice Hall; 2003.

    Google Scholar 

  67. Hogeweg P, Searls DB. The roots of bioinformatics in theoretical biology. PLoS Comput Biol. 2011;7(3):e1002021.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Sim AYL, Minary P, Levitt M. Modeling nucleic acids. Curr Opin Struct Biol. 2012;22(3):273–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Simonyan V, Goecks J, Mazumder R. Biocompute objects—a step towards evaluation and validation of biomedical scientific computations. PDA J Pharm Sci Technol. 2017;7(2):136–46.

    Article  Google Scholar 

  70. Saha S, Bhasin M, Raghava GP. Bcipep: a database of B-cell epitopes. BMC Genomics. 2005;6:79.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  71. Lund O, Nielsen M, Lundegaard C, Kesmir C, Brunak S. Immunological bioinformatics. Cambridge, MA: The MIT Press; 2005.

    Book  Google Scholar 

  72. Chiappelli F. Osteoimmunopathology: evidence-based perspectives from molecular biology to systems biology. New York: Springer; 2011.

    Book  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. UCLA School of Dentistry, Los Angeles, CA, USA

    Francesco Chiappelli, Allen Khakshooy & Nicole Balenton

Authors
  1. Francesco Chiappelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Allen Khakshooy
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nicole Balenton
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Francesco Chiappelli .

Editor information

Editors and Affiliations

  1. Department of Internal Medicine, University of South Florida, Tampa, FL, USA

    Paul Shapshak

  2. Department of Biotechnology, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India

    Seetharaman Balaji

  3. Biomedical Informatics 17, Irulan Sandy Annex, Pondicherry, Pondicherry, India

    Pandjassarame Kangueane

  4. Oral Biology and Medicine, CHS 63-090, UCLA School of Dentistry Oral Biology and Medicine, CHS 63-090, Los Angeles, CA, USA

    Francesco Chiappelli

  5. Department of Internal Medicine, University of South Florida, Tampa, FL, USA

    Charurut Somboonwit

  6. Department of Internal Medicine, University of South Florida, Tampa, FL, USA

    Lynette J. Menezes

  7. Department of Internal Medicine, University of South Florida, Tampa, FL, USA

    John T. Sinnott

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Chiappelli, F., Khakshooy, A., Balenton, N. (2019). Non-immune Modulators of Cellular Immune Surveillance to HIV-1 and Other Retroviruses: Future Artificial Intelligence-Driven Goals and Directions. In: Shapshak, P., et al. Global Virology III: Virology in the 21st Century. Springer, Cham. https://doi.org/10.1007/978-3-030-29022-1_2

Download citation

Publish with us

Policies and ethics

Search

Navigation